Papers with Entity matching
Match, Compare, or Select? An Investigation of Large Language Models for Entity Matching (2025.coling-main)
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| Challenge: | Entity matching (EM) is a critical step in entity resolution (ER). |
| Approach: | They propose a method that incorporates record interactions from different perspectives. |
| Outcome: | The proposed framework improves on 8 ER datasets and 10 LLMs and achieves higher efficiency and effectiveness. |
Learning from Natural Language Explanations for Generalizable Entity Matching (2024.emnlp-main)
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| Challenge: | Entity matching is the task of linking records from different sources that refer to the same real-world entity. |
| Approach: | They propose to "distill" LLM reasoning into smaller entity matching models via natural language explanations. |
| Outcome: | The proposed model distillation approach achieves strong performance on out-of-domain generalization tests (10.85% F-1). |
How to Talk to Language Models: Serialization Strategies for Structured Entity Matching (2025.findings-naacl)
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| Challenge: | Entity matching (EM) identifies whether two data records refer to the same entity . however, its performance heavily depends on how structured entities are “talked” through serialized text. |
| Approach: | They propose a novel serialization scheme for entities with complex relations in knowledge graphs based on random walks and use open-source LLMs to encode sampled semantic walks for matching. |
| Outcome: | The proposed scheme achieves leading performance on EM in canonical and heterogeneous KGs. |
CaRL-EM: Cost-Aware Reinforcement Learning for Entity Matching with LLMs (2026.acl-long)
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| Challenge: | Entity matching (EM) requires fine-grained contextual understanding and domain knowledge. |
| Approach: | They propose a reinforcement learning controller that manages LLM operations by combining multiple operators and a set of model capacities. |
| Outcome: | The proposed controller can be reused with different LLM backends at inference time without retraining. |